Search results for " pattern"

showing 10 items of 2245 documents

In vitro differentiation of murine hematopoietic progenitor cells toward the myeloid lineage occurs in response to Staphylococcus aureus and yeast sp…

2013

We have studied the effect of inactivated microbial stimuli (Candida albicans, Candida glabrata, Saccharomyces boulardii, and Staphylococcus aureus) on the in vitro differentiation of lineage negative (Lin−) hematopoietic progenitor mouse cells. Purified Lin− progenitors were co-cultured for 7 days with the stimuli, and cell differentiation was determined by flow cytometry analysis. All the stimuli assayed caused differentiation toward the myeloid lineage. S. boulardii and particularly C. glabrata were the stimuli that induced in a minor extent differentiation of Lin− cells, as the major population of differentiated cells corresponded to monocytes, whereas C. albicans and S. aureus induced …

Staphylococcus aureusMyeloidLineage (genetic)FarmacologíaPattern-recognition receptorsCandida glabratamedicine.disease_causeMicrobiologyMicrobiologySaccharomycesCandida albicansmedicineAnimalsMouse hematopoietic progenitorsCandida albicansbiologyCandida glabrataCell DifferentiationFlow CytometryHematopoietic Stem Cellsbiology.organism_classificationCoculture TechniquesYeastIn vitroMice Inbred C57BLSaccharomyces boulardiiInfectious Diseasesmedicine.anatomical_structureStaphylococcus aureusReceptors Pattern RecognitionHematopoietic progenitor cellsFemaleMicrobial Pathogenesis
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Spatio‐temporal classification in point patterns under the presence of clutter

2019

We consider the problem of detection of features in the presence of clutter for spatio-temporal point patterns. In previous studies, related to the spatial context, Kth nearest-neighbor distances to classify points between clutter and features. In particular, a mixture of distributions whose parameters were estimated using an expectation-maximization algorithm. This paper extends this methodology to the spatio-temporal context by considering the properties of the spatio-temporal Kth nearest-neighbor distances. For this purpose, we make use of a couple of spatio-temporal distances, which are based on the Euclidean and the maximum norms. We show close forms for the probability distributions o…

Statistics and Probability010504 meteorology & atmospheric sciencesComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONContext (language use)01 natural sciences010104 statistics & probabilitySpatio-temporalpoint patternsClutterExpectation–maximization algorithmEuclidean geometryEarthquakesPoint (geometry)clutter earthquakes EM algorithm features mixtures nearest‐neighbor distances spatio‐temporal point patterns0101 mathematicsEM algorithmFeatures0105 earth and related environmental sciencesspatio-temporal point patternSpatial contextual awarenessEcological Modelingmixturenearest-neighbor distanceComputingMethodologies_PATTERNRECOGNITIONearthquakeMixturesProbability distributionClutterfeatureSettore SECS-S/01 - StatisticaclutterNearest-neighbor distancesAlgorithmEnvironmetrics
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Block Based Deconvolution Algorithm Using Spline Wavelet Packets

2010

This paper presents robust algorithms to deconvolve discrete noised signals and images. The idea behind the algorithms is to solve the convolution equation separately in different frequency bands. This is achieved by using spline wavelet packets. The solutions are derived as linear combinations of the wavelet packets that minimize some parameterized quadratic functionals. Parameters choice, which is performed automatically, determines the trade-off between the solution regularity and the initial data approximation. This technique, which id called Spline Harmonic Analysis, provides a unified computational scheme for the design of orthonormal spline wavelet packets, fast implementation of the…

Statistics and ProbabilityApplied MathematicsSpline waveletCondensed Matter PhysicsDeconvolution · Wavelet packet · Spline · RegularityWavelet packet decompositionSpline (mathematics)Quadratic equationModeling and SimulationOrthonormal basisGeometry and TopologyComputer Vision and Pattern RecognitionDeconvolutionThin plate splineLinear combinationAlgorithmMathematics
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Regional Inequalities in Consumption Patterns: A Multilevel Approach to the Case of Italy

2007

Summary The main aim of this paper is to evaluate the disparities in the Italian regions on the demand side. In more detail, an attempt will be made to find if the consumption behaviour of Italian households is different in the regions. With this in mind, Istat's 2000 Italian Family Budget data set was analysed. The data in question, which were collected through a two-stage sample over Italy's 20 regions, contains information regarding the expenses of approximately 23,000 households. In this analysis, both households and regions are considered as units: households are nested in the regions so that the basic data structure is hierarchical. In order to take this hierarchical structure into ac…

Statistics and ProbabilityConsumption (economics)InequalitySettore SECS-S/02 - Statistica Per La Ricerca Sperimentale E Tecnologicamedia_common.quotation_subjectMultilevel modelSample (statistics)Context (language use)multilevel modelConsumption patternGeographyOrder (exchange)Income distributionEconometricsStatistics Probability and Uncertaintyregional inequalitiesLevel of analysismedia_commonDemographyInternational Statistical Review
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Weighted distance-based trees for ranking data

2017

Within the framework of preference rankings, the interest can lie in finding which predictors and which interactions are able to explain the observed preference structures, because preference decisions will usually depend on the characteristics of both the judges and the objects being judged. This work proposes the use of a univariate decision tree for ranking data based on the weighted distances for complete and incomplete rankings, and considers the area under the ROC curve both for pruning and model assessment. Two real and well-known datasets, the SUSHI preference data and the University ranking data, are used to display the performance of the methodology.

Statistics and ProbabilityDecision tree03 medical and health sciences0302 clinical medicine0504 sociology030225 pediatricsPreference dataStatisticsDecision treePruning (decision trees)University ranking dataDistance-based methodMathematicsWeighted distanceApplied Mathematics05 social sciencesUnivariate050401 social sciences methodsSUSHI dataComputer Science Applications1707 Computer Vision and Pattern RecognitionPreferenceComputer Science ApplicationsRankingRanking dataKemeny distanceSettore SECS-S/01 - StatisticaArea under the roc curve
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A spatially filtered mixture of β-convergence regressions for EU regions, 1980–2002

2007

Assessing regional growth and convergence across Europe is a matter of primary relevance. Empirical models that do not account for structural heterogeneities and spatial effects may face serious misspecification problems. In this work, a mixture regression approach is applied to the beta-convergence model, in order to produce an endogenous selection of regional growth patterns. A priori choices, such as North-South or centre-periphery divisions, are avoided. In addition to this, we deal with the spatial dependence existing in the data, applying a local filter to the data. The results indicate that spatial effects matter, and either absolute, conditional, or club convergence, if extended to …

Statistics and ProbabilityEconomics and EconometricsSmall numberEmpirical modellingSample (statistics)Filter (signal processing)Mathematics (miscellaneous)Rate of convergenceConvergence (routing)StatisticsOutlierEconometricsSpatial dependenceSettore SECS-P/01 - Economia PoliticaRegional growth - Convergence patterns - Mixture regression - Spatial effectsSocial Sciences (miscellaneous)MathematicsEmpirical Economics
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On 1-Laplacian Elliptic Equations Modeling Magnetic Resonance Image Rician Denoising

2015

Modeling magnitude Magnetic Resonance Images (MRI) rician denoising in a Bayesian or generalized Tikhonov framework using Total Variation (TV) leads naturally to the consideration of nonlinear elliptic equations. These involve the so called $1$-Laplacian operator and special care is needed to properly formulate the problem. The rician statistics of the data are introduced through a singular equation with a reaction term defined in terms of modified first order Bessel functions. An existence theory is provided here together with other qualitative properties of the solutions. Remarkably, each positive global minimum of the associated functional is one of such solutions. Moreover, we directly …

Statistics and ProbabilityFOS: Computer and information sciencesComputer scienceNoise reductionComputer Vision and Pattern Recognition (cs.CV)Bayesian probabilityComputer Science - Computer Vision and Pattern Recognition02 engineering and technology01 natural sciencesTikhonov regularizationsymbols.namesakeMathematics - Analysis of PDEsOperator (computer programming)Rician fading0202 electrical engineering electronic engineering information engineeringFOS: MathematicsApplied mathematicsMathematics - Numerical Analysis0101 mathematicsApplied Mathematics010102 general mathematicsNumerical Analysis (math.NA)Condensed Matter PhysicsNonlinear systemModeling and Simulationsymbols020201 artificial intelligence & image processingGeometry and TopologyComputer Vision and Pattern RecognitionLaplace operatorBessel functionAnalysis of PDEs (math.AP)
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From deterministic cellular automata to coupled map lattices

2016

A general mathematical method is presented for the systematic construction of coupled map lattices (CMLs) out of deterministic cellular automata (CAs). The entire CA rule space is addressed by means of a universal map for CAs that we have recently derived and that is not dependent on any freely adjustable parameters. The CMLs thus constructed are termed real-valued deterministic cellular automata (RDCA) and encompass all deterministic CAs in rule space in the asymptotic limit $\kappa \to 0$ of a continuous parameter $\kappa$. Thus, RDCAs generalize CAs in such a way that they constitute CMLs when $\kappa$ is finite and nonvanishing. In the limit $\kappa \to \infty$ all RDCAs are shown to ex…

Statistics and ProbabilityGeneral Physics and AstronomyFOS: Physical sciencesPattern Formation and Solitons (nlin.PS)Space (mathematics)01 natural sciences010305 fluids & plasmasLinear stability analysis0103 physical sciencesLimit (mathematics)Statistical physics010306 general physicsMathematical PhysicsBifurcationPhysicsCellular Automata and Lattice Gases (nlin.CG)Quiescent stateStatistical and Nonlinear PhysicsNonlinear Sciences - Chaotic DynamicsNonlinear Sciences - Pattern Formation and SolitonsCellular automatonNonlinear Sciences - Adaptation and Self-Organizing SystemsHomogeneousModeling and SimulationContinuous parameterChaotic Dynamics (nlin.CD)Adaptation and Self-Organizing Systems (nlin.AO)Nonlinear Sciences - Cellular Automata and Lattice Gases
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Decomposable multiphase entropic descriptor

2013

To quantify degree of spatial inhomogeneity for multiphase materials we adapt the entropic descriptor (ED) of a pillar model developed to greyscale images. To uncover the contribution of each phase we introduce the suitable 'phase splitting' of the adapted descriptor. As a result, each of the phase descriptors (PDs) describes the spatial inhomogeneity attributed to each phase-component. Obviously, their sum equals to the value of the overall spatial inhomogeneity. We apply this approach to three-phase synthetic patterns. The black and grey components are aggregated or clustered while the white phase is the background one. The examples show how the valuable microstuctural information related…

Statistics and ProbabilityLength scaleWhite phaseDegree (graph theory)Statistical Mechanics (cond-mat.stat-mech)Phase (waves)PillarValue (computer science)FOS: Physical sciencesCondensed Matter PhysicsGrayscaleCombinatoricsComputer Science::Computer Vision and Pattern RecognitionStatistical physicsCondensed Matter - Statistical MechanicsInteger (computer science)Mathematics
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Local inhomogeneous second-order characteristics for spatio-temporal point processes occurring on linear networks

2022

AbstractPoint processes on linear networks are increasingly being considered to analyse events occurring on particular network-based structures. In this paper, we extend Local Indicators of Spatio-Temporal Association (LISTA) functions to the non-Euclidean space of linear networks, allowing to obtain information on how events relate to nearby events. In particular, we propose the local version of two inhomogeneous second-order statistics for spatio-temporal point processes on linear networks, the K- and the pair correlation functions. We put particular emphasis on the local K-functions, deriving come theoretical results which enable us to show that these LISTA functions are useful for diagn…

Statistics and ProbabilityLocal Indicators of Spatio-Temporal Associationlocal propertiessecond-order characteristicsresidual analysislinear networksspatio-temporal point patternsStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaLinear networks Local Indicators of Spatio-temporal Association Local properties Residual analysis Second-order characteristics Spatio-temporal point patterns
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